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The importance of human population characteristics in modeling Aedes aegypti distributions and assessing risk of mosquito-borne infectious diseases

Overview of attention for article published in Tropical Medicine & Health, November 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
117 Mendeley
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Title
The importance of human population characteristics in modeling Aedes aegypti distributions and assessing risk of mosquito-borne infectious diseases
Published in
Tropical Medicine & Health, November 2017
DOI 10.1186/s41182-017-0078-1
Pubmed ID
Authors

Julie F. Obenauer, T. Andrew Joyner, Joseph B. Harris

Abstract

The mosquito Aedes aegypti has long been a vector for human illness in the Southeastern United States. In the past, it has been responsible for outbreaks of dengue, chikungunya, and yellow fever and, very recently, the Zika virus that has been introduced to the region. Multiple studies have modeled the geographic distribution of Ae. aegypti as a function of climate factors; however, this ignores the importance of humans to the anthropophilic biter. Furthermore, Ae. aegypti thrives in areas where humans have created standing water sites, such as water storage containers and trash. As models are developed to examine the potential impact of climate change, it becomes increasingly important to include the most comprehensive set of predictors possible. This study uses Maxent, a species distribution model, to evaluate the effects of adding poverty and population density to climate-only models. Performance was evaluated through model fit statistics, such as AUC, omission, and commission, as well as individual variable contributions and response curves. Models which included both population density and poverty exhibited better predictive power and produced more precise distribution maps. Furthermore, the two human population characteristics accounted for much of the model contribution-more so than climate variables. Modeling mosquito distributions without accounting for their dependence on local human populations may miss factors that are very important to niche realization and subsequent risk of infection for humans. Further research is needed to determine if additional human characteristics should be evaluated for model inclusion.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 117 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 22%
Student > Master 18 15%
Other 12 10%
Student > Bachelor 10 9%
Student > Doctoral Student 9 8%
Other 20 17%
Unknown 22 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 19%
Environmental Science 16 14%
Medicine and Dentistry 12 10%
Biochemistry, Genetics and Molecular Biology 9 8%
Social Sciences 7 6%
Other 24 21%
Unknown 27 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 January 2018.
All research outputs
#7,063,283
of 22,564,527 outputs
Outputs from Tropical Medicine & Health
#89
of 358 outputs
Outputs of similar age
#124,551
of 339,922 outputs
Outputs of similar age from Tropical Medicine & Health
#13
of 30 outputs
Altmetric has tracked 22,564,527 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 358 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,922 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.